Myshkin Ingawale

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Myshkin Ingawale is an author.

Publications

Only those publications related to wikis are shown here.
Title Keyword(s) Published in Language DateThis property is a special property in this wiki. Abstract R C
Network analysis of user generated content quality in Wikipedia Hubs
Network analysis
Quality
Social computing
Social media
Structural holes
Web sites
Wikipedia
Wiki
Online Information Review English 2013 Purpose - Social media platforms allow near-unfettered creation and exchange of user generated content (UGC). Drawing from network science, the purpose of this paper is to examine whether high and low quality UGC differ in their connectivity structures in Wikipedia (which consists of interconnected user generated articles). Design/methodology/approach - Using Featured Articles as a proxy for high quality, a network analysis was undertaken of the revision history of six different language Wikipedias, to offer a network-centric explanation for the emergence of quality in UGC. Findings - The network structure of interactions between articles and contributors plays an important role in the emergence of quality. Specifically the analysis reveals that high-quality articles cluster in hubs that span structural holes. Research limitations/implications - The analysis does not capture the strength of interactions between articles and contributors. The implication of this limitation is that quality is viewed as a binary variable. Extensions to this research will relate strength of interactions to different levels of quality in UGC. Practical implications - The findings help harness the "wisdom of the crowds" effectively. Organisations should nurture users and articles at the structural hubs from an early stage. This can be done through appropriate design of collaborative knowledge systems and development of organisational policies to empower hubs. Originality/value - The network centric perspective on quality in UGC and the use of a dynamic modelling tool are novel. The paper is of value to researchers in the area of social computing and to practitioners implementing and maintaining such platforms in organisations. Copyright 0 0
Network Analysis of User Generated Content Quality in Wikipedia Wikipedia
Network analysis
Social computing
Structural holes
User generated content
Quality
Online Information Review 2012 Social media platforms allow near-unfettered creation and exchange of User Generated Content (UGC). We use Wikipedia, which consists of interconnected user generated articles. Drawing from network science, we examine whether high and low quality UGC in Wikipedia differ in their connectivity structures. Using featured articles as a proxy for high quality, we undertake a network analysis of the revision history of six different language Wikipedias to offer a network-centric explanation for the emergence of quality in UGC. The network structure of interactions between articles and contributors plays an important role in the emergence of quality. Specifically, the analysis reveals that high quality articles cluster in hubs that span structural holes. The analysis does not capture the strength of interactions between articles and contributors. The implication of this limitation is that quality is viewed as a binary variable. Extensions to this research will relate strength of interactions to different levels of quality in user generated content. Practical implications Our findings help harness the ‘wisdom of the crowds’ effectively. Organizations should nurture users and articles at the structural hubs, from an early stage. This can be done through appropriate design of collaborative knowledge systems and development of organizational policies to empower hubs. Originality The network centric perspective on quality in UGC and the use of a dynamic modeling tool are novel. The paper is of value to researchers in the area of social computing and to practitioners implementing and maintaining such platforms in organizations. 0 0
Persistence of Cultural Norms in Online Communities: The Curious Case of WikiLove Online community
Persistence of norms
Epidemiology
Network science
PACIS 2009: Pacific Asia Conference on Information Systems 2009 Tremendous progress in information and communication technologies in the last two decades has enabled the phenomenon of Internet-based groups and collectives, generally referred to as online communities. Many online communities have developed distinct cultures of their own, with accompanying norms. A particular research puzzle is the persistence and stability of such norms in online communities, even in the face of often exponential growth rates in uninitiated new users. We propose a network-theoretic approach to explain this persistence. Our approach consists of modelling the online community as a network of interactions, and representing cultural norms as transmissible ideas (or ‘memes’) propagating through this network. We argue that persistence of a norm over time depends, amongst other things, on the structure of the network through which it propagates. Using previous results from Network Science and Epidemiology, we show that certain structures are better than others to ensure persistence: namely, structures which have scale-free degree distributions and assortative mixing. We illustrate this theory using the case of the community of contributors at Wikipedia, a collaboratively generated online encyclopaedia. 0 0
Persistence of cultural norms in online communities: The curious case of wikilove Cultural norms
Online community
Social production
Wikipedia
PACIS 2009 - 13th Pacific Asia Conference on Information Systems: IT Services in a Global Environment English 2009 Tremendous progress in information and communication technologies in the last two decades has enabled the phenomenon of Internet-based groups and collectives, generally referred to as online communities. Many online communities have developed distinct cultures of their own, with accompanying norms. A particular research puzzle is the persistence and stability of such norms in online communities, even in the face of often exponential growth rates in uninitiated new users. We propose a network-theoretic approach to explain this persistence. Our approach consists of modelling the online community as a network of interactions, and representing cultural norms as transmissible ideas (or 'memes') propagating through this network. We argue that persistence of a norm over time depends, amongst other things, on the structure of the network through which it propagates. Using previous results from Network Science and Epidemiology, we show that certain structures are better than others to ensure persistence: namely, structures which have scale-free degree distributions and assortative mixing. We illustrate this theory using the case of the community of contributors at Wikipedia, a collaboratively generated online encyclopaedia. 0 0
The Small Worlds of Wikipedia: Implications for Growth, Quality and Sustainability of Collaborative Knowledge Networks Knowledge networks
Interaction networks
Small-worlds
AMCIS 2009: Americas Conference on Information Systems 2009 This work is a longitudinal network analysis of the interaction networks of Wikipedia, a free, user-led collaborativelygenerated online encyclopedia. Making a case for representing Wikipedia as a knowledge network, and using the lens of contemporary graph theory, we attempt to unravel its knowledge creation process and growth dynamics over time. Typical small-world characteristics of short path-length and high clustering have important theoretical implications for knowledge networks. We show Wikipedia’s small-world nature to be increasing over time, while also uncovering power laws and assortative mixing. Investigating the process by which an apparently un-coordinated, diversely motivated swarm of assorted contributors, create and maintain remarkably high quality content, we find an association between Quality and Structural Holes. We find that a few key high degree, cluster spanning nodes - ‘hubs’ - hold the growing network together, and discuss implications for the networks’ growth and emergent quality. 0 0
The small worlds of wikipedia: Implications for growth, quality and sustainability of collaborative knowledge networks Collaborative knowledge Networks
Network theory
Small-worlds
Wikipedia
15th Americas Conference on Information Systems 2009, AMCIS 2009 English 2009 This work is a longitudinal network analysis of the interaction networks of Wikipedia, a free, user-led collaborativelygenerated online encyclopedia. Making a case for representing Wikipedia as a knowledge network, and using the lens of contemporary graph theory, we attempt to unravel its knowledge creation process and growth dynamics over time. Typical small-world characteristics of short path-length and high clustering have important theoretical implications for knowledge networks. We show Wikipedia's small-world nature to be increasing over time, while also uncovering power laws and assortative mixing. Investigating the process by which an apparently un-coordinated, diversely motivated swarm of assorted contributors, create and maintain remarkably high quality content, we find an association between Quality and Structural Holes. We find that a few key high degree, cluster spanning nodes - 'hubs' - hold the growing network together, and discuss implications for the networks' growth and emergent quality. 0 0
Understanding the wikipedia phenomenon: A case for agent based modeling Agent based modeling
Collaboration
Knowledge management
Multi-agent systems
Wikipedia
International Conference on Information and Knowledge Management, Proceedings English 2008 Wikipedia, the user led and monitored "open" encyclopedia has been an undoubted popular success. Of particular interest are the diffusion process of the innovation throughout the "contributor" community, and the question as to why unpaid, often well qualified, volunteers contribute content and time. Explanations for 'altruistic' contributor behavior based on the positivistic paradigm, and with roots in organizational psychology, while heavily researched and documented, have not been readily transferable to quantitative models of sufficient predictive value, in relation to Wikipedia's metrics. For despite the wide range of types, ages, locations and motivations of its contributors and seekers, investigators on Wikipedia have identified certain definite and often surprisingly universal trends ('laws') in its overall growth curve, organization structure, community and article formation. Models based on aggregated top-level relationships between entities on and around wikipedia suffer from assuming relationships between these entities as inputs to the wikipedia process, rather than emergent phenomena that evolve and change with the output. We argue for an Agent Based Model of Wikipedia, with the end objective of our work being a tool with diagnostic and/or prescriptive value for decision makers in organizations using or planning to use Knowledge Management Systems. Copyright 2008 ACM. 0 0
Understanding the wikipedia phenomenon: a case for agent based modeling Agent based modeling
Collaboration
Knowledge management
Multi-agent systems
Wikipedia
PIKM English 2008 0 0